Defines the S11 yardstick BEFORE either stack exists: pinned commons-ref
as identical input, metrics M1-M4, the verbatim liveness-asymmetry
declaration, five binding LLM non-determinism rules for S10/S11, and a
ban on comparing offline numbers with live numbers.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AaQCFnfsh3tfq1VfzdJpoi
Findings 4-7 from the 2026-07-02 status analysis, per the session plan (S1):
- CHANGELOG rewritten truthfully (was: 'Plan phase - no framework code yet')
- README stack line names the split GA packages, not the agent-framework meta-package
- CLAUDE.md: MCP downgraded to extension point (in-process FunctionTool is the default seam)
- Verdict conflict semantics documented as chosen (store first-write-wins per id,
disk/wiki last-write-wins per file; full B10 taxonomy deliberately deferred)
- docs/extending.md: explicit 90%-principle cut-list (B10, B11, U12, U14, concurrent fan-out)
- .gitignore covers .trekexecute-progress-* (docs/.DS_Store was already untracked/ignored -
the plan's git rm --cached assumption was stale; no-op)
No code behavior changed (docstring only in verdicts.py). Suite 152/4 green, mypy clean,
ruff format --check clean.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AaQCFnfsh3tfq1VfzdJpoi
Nordstjerne fra design-samtale 2026-06-26. Konsoliderer: 8-stegs sverm-loop,
trelagsmodell (OKF-kontekst/output-inbox/promoteringsgate), to feedback-
tidsskalaer (kort synkron + lang fil-basert/gjenopptakbar), OKF/LLM-Wiki
datagrunnlag (web-verifisert mot Google knowledge-catalog), den samlende
diagnosen (tilbakemelding-inn-i-prompt-dataflyt mangler 3 steder), invarianter,
testbar "ferdig", delt eksempel for begge repo, fase-nedbrytning. 2 Mermaid-
diagrammer. STATE peker hit. R1 besluttet (shared/-dir nå). Domene lener mot
energieffektivisering (lærings-overflate > FinOps' for-deterministiske kjerne).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019any9zfGNNwWJPX5Zq2QRz
Two independent grounded passes (installed-source introspection + official MS
Learn via MCP) produce a per-need adopt/keep decision table for using MAF
features well in Fase 2, instead of reinventing them.
Headline: Microsoft's Workflows "State Isolation" page documents verbatim the
exact footgun Spike B(b) found today — a reused Workflow accumulates agent
threads across runs; the fix is a fresh-instance-per-run factory. Our
fresh_workflow() IS the official pattern.
Key verdicts: ADOPT real UsageDetails token counts + a budget ChatMiddleware +
native builder round caps + GA @tool/MCP + observability; KEEP the hand-rolled
structural VerdictStore and inline validator (MAF memory/eval are the wrong
shape); ROLL a tiny role->deployment map (declarative is preview/not installed).
Corrections recorded: CLAUDE.md "Magentic experimental" stands at doc-level (no
code gate); Spike D extend_instructions is two-arg (source_id, instructions).
Skills answer: method-as-Skill yes (MAF consumes SKILL.md natively, experimental);
MAF-docs-mirror Skill no (rots vs live MCP); the digest lives in this map.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Fif1r1En5W542HbZV88yMH
/trekreview flagged the Spike B(b) fan-out experiment as BROKEN_SUCCESS_CRITERION
(BLOCKER): it asserted a per-client call_count reached 3 on a reused instance vs
1 on a fresh one — a tautology true for any un-reset mutable counter, independent
of MAF, that never exercised the real G2/B7 shared-Workflow state-corruption
footgun. It was a false-confirm of a de-risk assumption.
Rebuilt to observe genuine MAF thread state via the messages each participant
RECEIVES (new FakeChatClient.received_texts seam):
- shared_instance_conversation_bleed: a reused built ConcurrentBuilder Workflow
accumulates the conversation across .run() calls — run N's participants receive
runs 0..N-1's prompts/replies (measured [[p0],[p0,p1],[p0,p1,p2]], strictly
monotonic) => genuine cross-run contamination.
- fresh_instance_conversation_isolation: a fresh instance per run gives each a
clean thread => each participant sees only its own project ([[p0],[p1],[p2]]).
Assumption now CONFIRMED with a meaningful observable. findings-b.md gains a
Method note recording why it was rebuilt; README rows updated.
Also fixes the MINOR: a_groupchat.run_live now mkdirs the findings dir before
write_text so a post-disposal run does not lose the measured result.
Gate green: ruff check + format, mypy src, pytest 48 passed / 1 skipped.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Fif1r1En5W542HbZV88yMH
Framework-neutral narrative of what portfolio-optimiser aims to achieve and the
two hypothesised approaches to the same method. Claude Agent SDK paragraphs
corrected by the user: the SDK spans both emergent (one agent + subagents) and
explicit orchestration (hand-written or agent-authored workflow script with a
non-LLM validator gate). The real difference vs MAF is ready-made named
constructs vs building blocks — not emergent vs explicit.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Fif1r1En5W542HbZV88yMH
Verified comparison of Microsoft Agent Framework (ground-truth introspection of
installed agent-framework-core 1.9.0 + Microsoft Learn) and Claude Agent SDK
(Anthropic docs + npm/PyPI). Grounds decision D7: rebuild the same method on
Claude Agent SDK as a separate sibling repo, in sequence, sharing only the
spec + golden/conformance suite — not orchestration code.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Fif1r1En5W542HbZV88yMH
Privat MS-tenant tilgjengelig men kostnadstak: lokal profil default i
utvikling, Foundry/Azure kun målrettet/minimal, ingen tunge test-kjøringer.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01H9FyyENxebxVThjrn9et8C
